Bottom Line:
Control energy savings due to this MHT idea with respect to a conventional helicopter are calculated.Parameters of helicopter FCS and dimensions of MHT are simultaneously optimized using a stochastic optimization method, namely, simultaneous perturbation stochastic approximation (i.e., SPSA).In order to observe improvement in behaviors of classical controls closed loop analyses are done.

ABSTRACTHelicopter moving horizontal tail (i.e., MHT) strategy is applied in order to save helicopter flight control system (i.e., FCS) energy. For this intention complex, physics-based, control-oriented nonlinear helicopter models are used. Equations of MHT are integrated into these models and they are together linearized around straight level flight condition. A specific variance constrained control strategy, namely, output variance constrained Control (i.e., OVC) is utilized for helicopter FCS. Control energy savings due to this MHT idea with respect to a conventional helicopter are calculated. Parameters of helicopter FCS and dimensions of MHT are simultaneously optimized using a stochastic optimization method, namely, simultaneous perturbation stochastic approximation (i.e., SPSA). In order to observe improvement in behaviors of classical controls closed loop analyses are done.

Mentions:
The adaptive SPSA algorithm summarized in Section 6 was applied in order to solve the simultaneous trimming and design problem using the SPSA parameters of S = 5, λ = 0.602, a = 500, d = 20, and Θ = 0.101 via MATLAB software. For this design problem the algorithm was very effective in rapidly decreasing the helicopter FCS energy, J, converging quickly to a stable value, as seen in Figure 4 (see Table 2 for optimum MHT control trim values). Moreover, the FCS energy corresponding to the system obtained using simultaneous trimming and design was 59.4% lower than the FCS energy of system obtained using classical helicopter and traditional OVC (meaning that %J = 59.4%). The vector of trim values obtained after applying simultaneous trimming and design situation was(15)x0 MHT40 kts=0.2830,0.0041,−0.1675,0.4826︸θ00,θc0,θs0,θT0, −0.0620,0.070,︸ϕA0,θA00.0849,0.1348,−0.0027,0︸β00,βc0,βs0,βd0, 0.08634,−0.0014,−0.0123,0︸ζ00,ζc0,ζs0,ζd0,1.1942,6.6766,9.3000︸χ0,λ00,λc0T.

Mentions:
The adaptive SPSA algorithm summarized in Section 6 was applied in order to solve the simultaneous trimming and design problem using the SPSA parameters of S = 5, λ = 0.602, a = 500, d = 20, and Θ = 0.101 via MATLAB software. For this design problem the algorithm was very effective in rapidly decreasing the helicopter FCS energy, J, converging quickly to a stable value, as seen in Figure 4 (see Table 2 for optimum MHT control trim values). Moreover, the FCS energy corresponding to the system obtained using simultaneous trimming and design was 59.4% lower than the FCS energy of system obtained using classical helicopter and traditional OVC (meaning that %J = 59.4%). The vector of trim values obtained after applying simultaneous trimming and design situation was(15)x0 MHT40 kts=0.2830,0.0041,−0.1675,0.4826︸θ00,θc0,θs0,θT0, −0.0620,0.070,︸ϕA0,θA00.0849,0.1348,−0.0027,0︸β00,βc0,βs0,βd0, 0.08634,−0.0014,−0.0123,0︸ζ00,ζc0,ζs0,ζd0,1.1942,6.6766,9.3000︸χ0,λ00,λc0T.

Bottom Line:
Control energy savings due to this MHT idea with respect to a conventional helicopter are calculated.Parameters of helicopter FCS and dimensions of MHT are simultaneously optimized using a stochastic optimization method, namely, simultaneous perturbation stochastic approximation (i.e., SPSA).In order to observe improvement in behaviors of classical controls closed loop analyses are done.

ABSTRACTHelicopter moving horizontal tail (i.e., MHT) strategy is applied in order to save helicopter flight control system (i.e., FCS) energy. For this intention complex, physics-based, control-oriented nonlinear helicopter models are used. Equations of MHT are integrated into these models and they are together linearized around straight level flight condition. A specific variance constrained control strategy, namely, output variance constrained Control (i.e., OVC) is utilized for helicopter FCS. Control energy savings due to this MHT idea with respect to a conventional helicopter are calculated. Parameters of helicopter FCS and dimensions of MHT are simultaneously optimized using a stochastic optimization method, namely, simultaneous perturbation stochastic approximation (i.e., SPSA). In order to observe improvement in behaviors of classical controls closed loop analyses are done.